Software Engineer (Big Data) , Recommendation Ecosystem Infrastructure (ByteDance Singapore) Te[...]

Pangleglobal; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

ByteDance Singapore is hiring a Software Engineer (Big Data) for the Recommendation Ecosystem Infrastructure to design and implement real-time data systems for large-scale recommendations.

You will build flexible storage and computing models, troubleshoot production failures, and contribute to distributed streaming frameworks. Requires strong coding skills and deep experience with Flink and data lake tech; opportunity to work on PB-scale data systems in a fast-paced environment.

Qualifications

• ,

Responsibilities

• Design and implement real‑time (streaming computing) data systems for large‑scale recommendation systems.
• Create flexible, scalable, stable, and high‑performance storage systems and computing models.
• Troubleshoot production system failures and design and implement necessary mechanisms and tools to ensure overall stability of the production systems.
• Construct industry‑leading streaming computing frameworks and other distributed systems to provide reliable infrastructure for massive data and large‑scale business systems.
• Research, design, and develop computer and network software or specialised utility programs.
• Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.
• Update software, enhance existing software capabilities, and develop and direct software testing and validation procedures.
• Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.

Skills

Java

C++

Scala

Python

Streaming computing

Troubleshooting

Learning mindset

Tools

FlinkDataStream

FlinkSQL

FlinkCheckpoint

FlinkState

Hudi

Iceberg

DeltaLake

YARN

Job description

Software Engineer (Big Data), Recommendation Ecosystem Infrastructure (ByteDance Singapore)

Employment Type: Regular

Job Code: A211442

Responsibilities

• Design and implement real‑time (streaming computing) data systems for large‑scale recommendation systems.
• Create flexible, scalable, stable, and high‑performance storage systems and computing models.
• Troubleshoot production system failures and design and implement necessary mechanisms and tools to ensure overall stability of the production systems.
• Construct industry‑leading streaming computing frameworks and other distributed systems to provide reliable infrastructure for massive data and large‑scale business systems.
• Research, design, and develop computer and network software or specialised utility programs.
• Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis.
• Update software, enhance existing software capabilities, and develop and direct software testing and validation procedures.
• Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements.

Qualifications

• Minimum Qualifications
  • Proficient in programming languages like Java, C++, Scala, Python.
  • Strong coding and troubleshooting skills.
  • At least 3 years of relevant experience.
  • Deep understanding of streaming computing systems, with formal production experience in developing TB‑level Flink real‑time computing systems. Proficient in modules such as FlinkDataStream, FlinkSQL, FlinkCheckpoint, FlinkState, and preferably experience reading Flink source code.
  • Experience in data lake development is preferred. Familiar with at least one data lake technology such as Hudi, Iceberg, DeltaLake, and preferably experience reading their source code.
  • Willingness to tackle problems without clear answers, with a strong passion for learning new technologies.
• Preferred Qualifications
  • Experience in handling PB‑level data is a plus.
  • Familiarity with other big data systems is preferred, including YARN, K8S, Spark, SparkSQL, Kudu, and others.
  • Experience in storage systems such as Hbase, Cassandra, RocksDB.